code: def test_gain():
      opts = get_config()
      gain_db = -20
      setattr(opts, "audio_augmentation.gain.levels", [gain_db])
      augmenter = Gain(opts)
      dummy_audio = torch.randint(
          1, 16000, (1, 16000), dtype=torch.int16
      )
      data = {
          "samples": {"audio": dummy_audio},
          "metadata": {"audio_fps": 16000},
      }
      augmented = augmenter(data)
      assert (
          data["samples"]["audio"].shape
          == augmented["samples"]["audio"].shape
      )
      assert (
          augmented["samples"]["audio"] != dummy_audio
      ).float().sum() > 0.99 * dummy_audio.numel()
      assert (
          torch.abs(
              (augmented["samples"]["audio"] / dummy_audio)
              .float()
              .sum()
              - 10 ** (gain_db / 20) * dummy_audio.numel()
          )
          < 0.001
      )
  
file_path: ml-cvnets/tests/transforms/test_audio.py
imports: import copy
  import os
  import shutil
  import tempfile
  import pytest
  import scipy.io.wavfile
  import torch
  from data.transforms.audio import AudioResample, Gain, LambdaAudio, MFCCs, Noise, Roll, SetFixedLength, StandardizeChannels
  from tests.configs import get_config
label_desc: Use image node_id 7 for calling a global function with example usage: test_gain() without return types